Ateneo - UPO

The course consists in a first part with topics related to descriptive statistics and in a second part that will concern the inferential statistics.

W.W. Daniel, CL. Cross Biostatistics, Tenth edition. John Wiley & Sons
Rosner B. Fundamentals of Biostatistics. Eighth edition. Brooks/Cole Pub Co

The course aims to: provide methodological issues related to descriptive and inferential statistics, select the appropriate statistical method to summarize study data, interpretation of the results

Basic knowledge in mathematics

Lectures, Classroom exercises

The Course material is available in the Moodle platform.
Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/services-students-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

Written exam. The exam aims to verify knowledge and skills acquired by the student through the solution of exercises and open questions concerning the course programme. Each exercise or question will be assigned a specific score, which will contribute to the determination of the final grade.

The frequency distribution. Measures of Central Tendency and dispersion. Properties of Probability. Probability distribution: the Poisson and normal distribution. Sampling distribution. Distribution of the sample mean. Confidence interval. Hypothesis testing: a single population mean, the difference between two population means, a single population proportion. Type I and type II error and the power of a test. Chi-square test. Odds ratio. The correlation coefficient and the regression model. Survival analysis.

Knowledge and understanding: to go in depth of statistical methods for the analysis of clinical data.
Ability to apply knowledge and understanding: translating theory into practice by concretely working at the solutions to exercises.
Decision-making autonomy: acquiring autonomy in decision to conduct the analysis of data obtained from surveys.
Communication skills: ability to communicate knowledge with clarity, scientific and methodological rigour.
Learning skills: dealing with the information obtained from clinical studies with the objective of collecting and organizing data and correctly interpreting the information.